Cardiac monitoring system with supraventricular tachycardia (SVT) classifications

ABSTRACT

In one example, a cardiac monitoring system comprises a processor to receive a segment of an electrocardiogram (ECG) signal of a patient, and a memory to store the segment of the ECG. The processor is configured to identify QRS complexes in the segment of the ECG signal, generate a supraventricular (SV) template for SV complexes in the QRS complexes, identify SV complexes in the QRS complexes using the template, identify normal sinus rhythm (NSR) complexes in the segment of the ECG signal, obtain an atrial template for atrial waveforms in the NSR complexes, measure a range of a P-wave of the atrial waveforms from the NSR complexes, save the measured P-waves, and classify the identified SV complexes as either atrial fibrillation (AF) or supraventricular tachycardia (SVT) using the atrial template. Other examples and related methods are also disclosed herein.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit of U.S. ProvisionalApplication No. 62/890,313 (C00003612.USP1) filed Aug. 22, 2019 and thebenefit of U.S. Provisional Application No. 62/891,216 (C00003614.USP1)filed Aug. 23, 2019. Said Application No. 62/890,313 and saidApplication No. 62/891,216 are hereby incorporated herein by referencein their entireties.

BACKGROUND

Cardiac monitoring systems can continuously monitor a patient'selectrocardiogram (ECG) signal to generate a rhythm classification.Because the ECG signals can be a mixture of multiple different QRSmorphologies, using only heart rate (HR) and HR variability can produceincorrect heart rhythm classification, especially in classifyingsupraventricular tachycardia (SVT) rhythms. For example, atrialfibrillation (AF) and SVT rhythms can have high HR variability, so acardiac monitoring system may have difficulty distinguishing between AFand SVT rhythms if only HR variability is used. A noisy ECG signal canincrease the difficulty. Existing rhythm methods based on RR intervalvariability may have a high percentage of AF false positive alarms dueto noise, PR interval variability, premature ventricular contractions(PVCs), and premature atrial contractions (PACs).

DESCRIPTION OF THE DRAWING FIGURES

Claimed subject matter is particularly pointed out and distinctlyclaimed in the concluding portion of the specification. However, suchsubject matter may be understood by reference to the following detaileddescription when read with the accompanying drawings in which:

FIG. 1 is a diagram of four electrocardiograms (ECG) monitoring vectorsused in an ECG monitoring device in accordance with one or moreembodiments.

FIG. 2 is diagram of a wearable cardioverter defibrillator (WCD) as anexample ECG monitoring device in accordance with one or moreembodiments.

FIG. 3 is a diagram of an identified QRS complex sampled waveform inaccordance with one or more embodiments.

FIG. 4 is a diagram of a method to identify a main template from aseries of QRS complexes in accordance with one or more embodiments.

FIG. 5 is a diagram illustrating RR intervals between QRS complexes inaccordance with one or more embodiments.

FIG. 6 is a diagram of a method to identify RR intervals between similarQRS complexes in accordance with one or more embodiments.

FIG. 7 is a diagram of an ECG signal showing distinctive depolarizationwaveforms in accordance with one or more embodiments.

FIG. 8 is a diagram of the ECG signal of FIG. 7 showing a differentscale including the HR variability of the ECG signal in accordance withone or more embodiments.

FIG. 9 is a diagram of a method for SVT rhythm classification inaccordance with one or more embodiments.

FIG. 10 is a diagram of an additional method for SVT rhythmclassification in accordance with one or more embodiments.

FIG. 11 is a diagram of example atrial templates including P-wavetemplates in accordance with one or more embodiments.

FIG. 12 is a diagram of additional examples of atrial templatesincluding P-wave templates in accordance with one or more embodiments.

It will be appreciated that for simplicity and/or clarity ofillustration, elements illustrated in the figures have not necessarilybeen drawn to scale. For example, the dimensions of some of the elementsmay be exaggerated relative to other elements for clarity. Further, ifconsidered appropriate, reference numerals have been repeated among thefigures to indicate corresponding and/or analogous elements.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth to provide a thorough understanding of claimed subject matter. Itwill, however, be understood by those skilled in the art that claimedsubject matter may be practiced without these specific details. In otherinstances, well-known methods, procedures, components and/or circuitshave not been described in detail.

In the following description and/or claims, the terms coupled and/orconnected, along with their derivatives, may be used. In particularembodiments, connected may be used to indicate that two or more elementsare in direct physical and/or electrical contact with each other.Coupled may mean that two or more elements are in direct physical and/orelectrical contact. However, coupled may also mean that two or moreelements may not be in direct contact with each other, but yet may stillcooperate and/or interact with each other. For example, “coupled” maymean that two or more elements do not contact each other but areindirectly joined together via another element or intermediate elements.Finally, the terms “on,” “overlying,” and “over” may be used in thefollowing description and claims. “On,” “overlying,” and “over” may beused to indicate that two or more elements are in direct physicalcontact with each other. It should be noted, however, that “over” mayalso mean that two or more elements are not in direct contact with eachother. For example, “over” may mean that one element is above anotherelement but not contact each other and may have another element orelements in between the two elements. Furthermore, the term “and/or” maymean “and”, it may mean “or”, it may mean “exclusive-or”, it may mean“one”, it may mean “some, but not all”, it may mean “neither”, and/or itmay mean “both”, although the scope of claimed subject matter is notlimited in this respect. In the following description and/or claims, theterms “comprise” and “include,” along with their derivatives, may beused and are intended as synonyms for each other.

Referring now to FIG. 1 is a diagram of an electrocardiogram (ECG)monitoring device using four ECG monitoring vectors in accordance withone or more embodiments. A cardiac monitoring system or device cancomprise a wearable cardioverter defibrillator (WCD) or a wearablecardiac monitor (WCM) that is configured to continuously monitor anelectrocardiogram (ECG) signal of a patient 110 and generate a rhythmdiscrimination. FIG. 1 shows the relationship between physical electrodeplacement and ECG vector naming conventions. Electrodes E1, E2, E3, andE4 are the single-ended monitored electrodes and RLD is the Right LegDrive electrode used to manage common mode noise.

In example shown in FIG. 1 , a patient 110 can wear a support structure112 that may comprise a wearable garment or vest or the like. In someexamples, support structure 112 can include four ECG electrodescomprising electrode 122 (E1), electrode 124 (E2), electrode 126 (E3),and electrode 128 (E4). In addition, support structure 112 can include acommon mode electrode 130 referred to as a right leg drive (RLD)electrode. The electrodes can couple with the ECG monitoring device suchas a WCD or a WCM to obtain the ECG signals of the patient 110. The ECGsignals can be digitized by the cardiac monitoring device for digitalprocessing.

In some examples, differential vectors can be formed by subtracting twodigitized ECG signals. ECG rhythm analysis then can be performed onthese four vectors. Vectors E12, E13, E34, and E24 are the differentialvectors that are derived from the single-ended vectors. Suchdifferential vectors may include, for example, vector (E24) 132, vector(E34) 134, vector (E12) 136, and vector (E13) 138. The defibrillatorshock vector 140 may be generated between the anterior defibrillationpad 104 and the posterior defibrillation pad 108. The ECG analysisalgorithm includes provisions for excluding vectors that have noise orwhen a leads-off condition or situation is detected. Monitoring fourvectors rather than monitoring two vectors is believed to contribute toenhanced ECG signal analysis and processing of the shock applicationalgorithm to reduce the number of false shock events.

In one or more embodiments, the signals from four ECG electrodes can becombined to form six different vectors. In some embodiments, an ECGmonitoring device can use four vectors for QRS complex analysis or heartrate analysis to determine if a shock should be applied. In someexamples, a WCD device can be capable of performing the analysis andshock application determination if one or more of the vectors is noisyor one or more of the ECG leads is in a lead-off condition wherein thelead is not contacting the patient's skin or is not sufficientlycontacting the patient's skin to allow an ECG signal to be obtained withthat ECG lead. In some embodiments, three ECG electrodes may be used andthree ECG vectors may be analyzed. In other embodiments, five or six ECGvectors may be analyzed using four ECG electrodes. In some embodiments,a single vector is used and analyzed. It should be noted that in generalan ECG monitoring device can use and analyze fewer than four vectors orgreater than four vectors, and the number of vectors can be increasedbeyond six vectors by using additional ECG electrodes, and the scope ofthe disclosed subject matter is not limited in this respect. In someexamples, an ECG monitoring device can use four channels out of sixpossible differential channels formed from four independent electrodesplaced around the chest of a patient 110. In other embodiments, adifferent number of channels, including only one channel, can be used.In embodiments where the ECG monitoring device comprises a WCM, adifferent number of electrodes can be used, often a reduced number ofelectrodes, or a different garment system can be used other than thegarment or support structure 112 shown in FIG. 1 .

In the example shown in FIG. 1 , the ECG electrodes can be placedcircumferentially around the torso of the patient 110 so that thegarment or support structure 112 can be used to ensure adequateelectrode-skin contact with the patient's skin. It should be noted thatother alternative electrode placements may be used, and the scope of thedisclosed subject matter is not limited in this respect. For example,adhesive electrode embodiments can provide flexibility in electrodeplacement in selected locations of the patient's body and may achievebetter signal pickup at these selected locations. For example, electrodelocations can be selected during a patient-fitting process in whichvarious electrode locations can be changed, and those locations withbetter or the best ECG signals can be selected, although the scope ofthe disclosed subject matter is not limited in this respect.

In some embodiments a cardiac monitoring device using the ECG electrodesas shown in FIG. 1 can be configured to detect similar QRS complexes toidentify the QRS complexes that are normally conducted through the AVnode. Such QRS complexes conducted through the AV node can be referredto herein as “normally conducted QRS complexes”. Because the ECG signalscan be a mixture of multiple different QRS morphologies, normallyconducted QRS complex identification can be used as described herein tomore accurately determine the rhythms including but not limited todetermining atrial fibrillation (AF) and the associated heart rate (HR)and HR variability, according to one or more embodiments.

According to some embodiments, a cardiac monitoring system or devicesuch as a Wearable Cardioverter Defibrillator (WCD) or a WearableCardiac Monitor (WCM) is configured to continuously monitor thepatient's ECG signal and generate a rhythm discrimination. In someembodiments the cardiac monitoring device can be configured to detectsimilar QRS complexes and their P-waves to identify the QRS complexesthat are normally conducted through the AV node, referred to herein asnormally conducted QRS complexes, and distinguish between differenttypes of SVT. Because the ECG signals can be a mixture of multipledifferent QRS morphologies and noise, normally conducted QRS complexidentification and RR interval and P-wave analysis is used to determinethe rhythms more accurately, including classifying SVT rhythms, inaccordance with one or more embodiments.

According to some embodiments, a cardiac monitoring device such as a WCDor a WCM can be configured to continuously monitor the patient's ECGsignal and detect normally conducted QRS complexes. For arrhythmias withHR in the VT zone, detecting normally conducted QRS complexes can beused to distinguish supraventricular-originated arrhythmias such as AFor SVT from ventricular-originated arrhythmias such as VT or VF. In someembodiments, the normally conducted QRS complexes can be detected bydetecting similar QRS complexes. In some embodiments, QRS similarity canbe detected by formulating a template of normally conducted QRScomplexes and determining a correlation between the formulated templateand detected QRS complexes. In other embodiments, QRS similarity can bedetermined using other approaches, for example comparing the width andamplitude of the QRS complexes. The accuracy of the rhythm analysis canbe affected by noise, so analyzing noisy QRS complexes can increasefalse alarms of the rhythm classification. By analyzing similar QRScomplexes as is done in embodiments discussed herein, noise effects canbe reduced because noise would tend to make QRS complexes less similar.This in turn tends to increase the accuracy of the rhythm classificationand reduce false positives.

Furthermore, normally conducted QRS arrhythmias are not shockablerhythms for a WCD. It is possible that if a conventional WCD mistakenlydiagnoses a normally conducted QRS rhythm as a shockable rhythm, itwould provide an unnecessary and potentially dangerous shock to thepatient.

In addition, as described below, for detectedsupraventricular-originated arrhythmias, meaning those with normallyconducted QRS complexes, the RR interval between consecutive normallyconducted QRS complexes and the morphology of their P-waves can beanalyzed to classify the rhythm into AF or various SVT rhythms, in someembodiments.

In some embodiments, the cardiac monitoring system can be used in othertypes of external monitoring devices, for example non-wearable externaldefibrillators such as those used by emergency medical technicians(EMTs), automated external defibrillators (AEDs), and hospitaldefibrillators, or in implanted devices. The cardiac monitoring systemof such embodiments may be deployed where monitored patients are beingtransported and causing movement between the ECG sensors and the portionof the patient that the sensors contact or are in high EMI environments,which can introduce noise to the patient's ECG.

Referring now to FIG. 2 , a diagram of a wearable cardioverterdefibrillator (WCD) as an example ECG or cardiac monitoring device inaccordance with one or more embodiments will be discussed. The WCD 200shown in FIG. 11 incorporates one or more of the features discussed forECG and QRS complex signal data detection and processing to detectatrial fibrillation (AF) as discussed herein. The ECG electrodes, E1122, E2 124, E3 126, and E4 128, can comprise silver or silver platedcopper electrodes that “dry” attach to the skin of the patient 110. TheECG electrodes provide ECG data to preamplifier 210. The preamplifier210 may have a wide dynamic range at its input, for example +/−1.1 Vwhich is much larger than the amplitude of the ECG signals which areabout 1 mV. The preamplifier 210 can include one or moreanalog-to-digital converters (ADCs) 212 to convert the ECG signals intoa digital format. A right-leg drive (RLD) electrode 130 can be used toprovide a common mode signal so that the ECG signal from the ECGelectrodes can be provided to preamplifier 210 as differential signals.The digital ECG signals are provided from the preamplifier 210eventually to a main processor 216 via an isolation barrier 214 whichoperates to electrically isolate the preamplifier 210 and the ECGsignals from the rest of the circuitry of WCD 200. In some examples, theECG signals are provided to preamp 210 and converted to a digital formatusing ADCs 212 at which point differential vectors are formed. Thedifferential vectors can then be filtered by digital filters 218 atwhich point QRS complexes can be detected.

The processor 216 processes the digital ECG data received from thepreamplifier 210 with one or more digital filters 218. Since thepreamplifier 210 has a wide dynamic range that is much wider than theamplitude range of the ECG signals, digital filters 218 can be utilizedto process the ECG data without concern for clipping the incomingsignals. One of the digital filters 218 can include a matched filter tofacilitate identification of QRS pulses in the incoming data stream. Thewide dynamic range of the preamplifier 210 allows at least most of theECG filtering to happen in software without the signal being clipped.Digital filters 218 can be very effective at removing artifacts from theECG data. In some examples, digital filters 218 can include one or morebandpass filters to filter the ECG data as discussed in further detailbelow.

In some examples, the processor 216 can apply a rhythm analysisalgorithm (RAA) 220 using QRS width information and heart rate dataextracted from the digital ECG data using a segment-based processinganalysis and the QRS width versus heart rate analysis to make a shock orno-shock determination. In some embodiments, segment-based processinganalysis can be performed as described in US 2019/0030351 A1 “WearableCardioverter Defibrillator (WCD) System Reacting to High-Frequency ECGNoise”. Said US 2019/0030351 A1 is hereby incorporated herein in itsentirety. The RAA 220 receives the digitized ECG signal and calculatesthe heart rate and QRS width for each segment. The digitized ECG signalis passed over the isolation barrier 214, and the heart rate is derivedfrom the digitized ECG signal. The heart rate and QRS width can be usedfor making a shock/no-shock decision for each segment, which then canlead to an alarm and a shock. In the event a shockable event isidentified, the processor 216 will open a tachycardia episode to startthe shock process. Unless the patient 110 provides a patient responseusing the stop button 222 or other user interface to send a stop shocksignal to the processor 216 to intervene before the shock is applied,the processor 216 can send a shock signal to the high voltage subsystem224 which will apply a defibrillation voltage across the defib frontelectrode 104 and the defib back electrode 108 to apply one or moretherapeutic shocks. In embodiments, the system will provide such shocksuntil there is no longer any shockable event (VT or VF), or until theenergy in a battery or capacitor of high voltage subsystem 224 isdepleted or after a predetermined number of shocks have been delivered.

In one or more embodiments of WCD 200, the digital filters 218 coupledwith the wide dynamic range of the preamplifier 210 can allow analysisof signals that otherwise would be clipped in systems with a morelimited dynamic range. In addition, the matched filter of the digitalfilters 218 preferentially highlights complexes similar to the patient'snormal rhythm. As a result, artifacts that otherwise may be difficult todiscriminate using other methods may be significantly attenuated by thematched filter to identify QRS complexes.

It should be noted that a subset of the elements of the WCD 200 of FIG.2 can be used as a cardiac or ECG monitoring device, or a WCM device,and optionally can be used in conjunction with the support structure 112of FIG. 1 . For example, a cardiac monitoring device can compriseelectrodes 122 through 128 (E1-E4) and electrode 130 (RLD), preamp 210,and processor 216, optionally with isolation barrier 214. For a WCMembodiment, the electrodes can be implemented as part of supportstructure 112. For a WCD embodiment, in addition to the ECG electrodesbeing in support structure 112, the support structure 112 can alsoinclude defibrillation front and back electrodes 104 and 108, and theWCD 200 can include the high voltage subsystem 224 and alert button.222. Other various elements or subsystems may be used in various othercombinations, as a subset or a superset of the elements shown in FIG. 2, as part of a cardiac or ECG monitoring system, WCM, WCD, AED, or thelike, to implement the functions of the particular embodiment of thecardiac monitoring system, and the scope of the disclosed subject matteris not limited in these respects.

Referring now to FIG. 3 , a diagram of an identified QRS complex sampledwaveform in accordance with one or more embodiments will be discussed.As discussed herein, an ECG monitoring device can be used to monitor ECGsignals of a patient 110 and to detect QRS complexes in the ECG signals.The QRS complexes can then be analyzed to detect when the patient isexperiencing AF. FIG. 3 shows an example QRS complex 300 waveformplotted in amplitude in millivolts (mV) versus time in milliseconds (ms)on the horizontal axis. The horizontal axis of FIG. 3 can be 2 ms persample point (500 samples per second) as one example. In the example QRScomplex 300 a minimum value is shown at point 310 which corresponds tothe S portion of the complex and can be referred to as a fiducial point.It is noted, however, that this is merely an example QRS complex, andthe minimum value can be at other points on the plotted QRS complex 300,and the scope of the disclosed subject matter is not limited in thisrespect. In addition, an example P-wave 302 is shown in the chart. Theatrial waveform is multiplied by 10 to make the P-wave 302 more visiblein the example shown in FIG. 3 , and the T-wave occurs after the QRScomplex. Sampled QRS complexes from the patent's ECG signals can beprocessed and analyzed as part of template based analysis as discussedbelow.

Referring now to FIG. 4 , a diagram of a method to identify a maintemplate from a series of QRS complexes in accordance with one or moreembodiments will be discussed. Although FIG. 4 shows one implementationof method 400, method 400 can include more or fewer operations thanshown and various other orders of the operations than shown, and thescope of the disclosed subject matter is not limited in these respects.The method 400 of FIG. 4 can be implemented as part of template based AFdetection. Current American Heart Association (AHA) guidelines definethe presence of atrial fibrillation (AF) as electrocardiographicdocumentation of absolutely irregular RR intervals and no discernible,distinct P waves lasting for at least 30 seconds. There are many ways AFburden can be defined, such as the duration of the longest AF episode,number of AF episodes, or the percentage of time the patient 110 is inAF during a certain monitoring period. Accordingly, an ECG or cardiacmonitoring device as discussed herein can measure the RR intervals andRR interval variability of consecutive normally conducted QRS complexes.Furthermore, since AF is not an immediately life-threatening arrhythmia,detecting the onset of AF is generally not critical. Accordingly, an ECGor cardiac monitoring device in accordance with one or more embodimentsneed not use real-time approaches for AF detection. In some examples, asegment-based approach with relatively long segments, for example overone minute long, can be used. It should be noted that a normal segmentlength can be about 4 or 5 seconds, and an analyzed segment can rangeanywhere from about 2 seconds up to about 2 minutes, and the scope ofthe disclosed subject matter is not limited in this respect.

In some embodiments, the ECG or cardiac monitoring device can comprise awearable cardioverter defibrillator such as WCD 200 having multiple ECGvectors from multiple electrodes for monitoring the patient 110. In someembodiments, a template of the selected channel can be formulated usingmethod 400, and AF can be detected as described with respect to FIG. 5below. In some embodiments, the template formulation process can beperformed when the patient's HR is detected to be below the VTthreshold, for example 110 beats per minute (bpm). The entire processcan be applied after template formulation for rhythm classification, forany HR. In some embodiments, some operations can be performed using theexisting template formed at a slower rate when the patient's HR isdetected to exceed the VT threshold. For example, a VT threshold can beset to 170 bpm in a WCD embodiment).

At operation 410, bandpass filtered ECG signals can be collected for afixed duration. As an example, the bandpass filter may have a bandwidthof about 8 Hz to about 25 Hz, and the fixed duration can be 60 seconds.At operation 412, a QRS detector can be applied to the filtered ECGsignal to identify locations of QRS complexes in the ECG signal. Anysuitable QRS detector can be used, for example, a QRS detector asdisclosed in published US patent application US 2018/0093102 A1 titledWEARABLE CARDIOVERTER DEFIBRILLATOR (WCD) WITH POWER-SAVING FUNCTION.Said published application US 2018/0093102 A1 is hereby incorporatedherein in its entirety. At operation 414, for each QRS complex thelocation of the minimum value can be identified as the fiducial point ina window, for example 160 ms starting from the detection point. Forexample, the minimum value can be the minimum value 310 shown in FIG. 3, and the waveform window can start 120 ms before the fiducial point andhave a duration of 240 ms.

At operation 416, the first QRS complex waveform can be set as the firsttemplate, and the template count can be set to a value of one (templatecount=1). In some examples, if there is an existing template, theexisting template optionally can be the starting template with atemplate count of one. At operation 418, the next QRS complex waveformcan be compared to the existing template waveform. The concept is toidentify similar QRS complexes. If the next QRS complex does not matchor is not correlated with the existing template or any template asdetermined at decision block 420, then the method continues by comparingthe next QRS complex to the template. If the current QRS complex is notcorrelated to any templates, then this QRS complex can be used as a newtemplate by adding this QRS complex as a new template at operation 428.The size or number of the templates can increase as more uncorrelatedQRS complexes are detected. If the next QRS complex waveform iscorrelated with the existing template as determined at decision block420, the existing template can be updated at block 422, and the templatecount can be incremented by one. The current QRS complex can becorrelated to multiple templates, and the count of each of the templatescan increase by one for each match. Optionally, in some embodiments, acomparison can be made with the fiducial points 310 to determinefiducial point shift, for example a minimum point −2 to minimum point+2. The fiducial point with the best match can be selected. In someexamples, the correlation decision can be made based on calculation of afeature correlation coefficient (FCC). In other examples, other measuresof correlation can be used, for example a sample correlation coefficient(SCC) wherein FCC is a squared version of SCC and the scope of thedisclosed subject matter is not limited in this respect. Other measuresof correlation or similarity can be utilized, for example comparison ofthe height and/or or width of the QRS complexes to the template, anormalized area difference method which measures the area differencebetween the QRS complex and the template divided by the area of thetemplate, a frequency domain analysis method, and so on. As an example,for one dataset {x1, . . . , xn} containing n values and another dataset{y1, . . . , yn} containing n values, then that formula for samplecorrelation coefficient (SCC) r is:

$r = {r_{xy} = \frac{\sum\limits_{i = 1}^{n}\;{\left( {x_{i} - \overset{\_}{x}} \right)\left( {y_{i} - \overset{\_}{y}} \right)}}{\sqrt{\sum\limits_{i = 1}^{n}\;\left( {x_{i} - \overset{\_}{x}} \right)^{2}}\sqrt{\sum\limits_{i = 1}^{n}\;\left( {y_{i} - \overset{\_}{y}} \right)^{2}}}}$

In the equation above, the x data values can correspond to the values ofa sampled QRS complex waveform being compared to the template, and the ydata values can correspond to the template to which a the QRS complexwaveform is being compared, wherein x and y are the average x and yvalues in each dataset. The SCC has value between −1 and 1 wherein forperfect match the SCC value will be 1. In some examples, if SCC>0.9,then the QRS complex can be considered as correlated with the template,and the existing template is updated by:Updated template=0.9*current template+0.1*current QRS complex

In the above equation, to arrive at the values of the updated template,the values in the current template are each multiplied by 0.9 and thevalues of the current QRS complex are multiplied by 0.1, then thecorresponding values are added to arrive at the values for the updatedtemplate. It should be noted that although weighting multipliers 0.9 and0.1 in the above example can be used for some embodiments, other valuesof multipliers can be used in other embodiments, for example 0.8 and 0.2or 0.95 and 0.005, and so on, and the scope of the disclosed subjectmatter is not limited in this respect. At operation 424, QRS complexescan continue to be compared to the existing template until all QRScomplexes have been compared and all templates have a template countvalue. The template having the highest template count, meaning the mostsimilarity to the greatest number of the QRS complexes in a givensegment of QRS complexes, can be selected at operation 426 to be themain template. If the highest template count is more than 50 percent ofthe number of detected QRS complexes in the segment, then the maintemplate is selected as the main template of this segment. Otherwise,the segment can be considered to be an unstable situation and thereforethe segment can be skipped. The main template can then be used toidentify normally conducted QRS complexes to detect AF using RRintervals in the normally conducted QRS complexes according to FIG. 6below. An example of an RR interval is shown in and described withrespect to FIG. 5 below.

Referring now FIG. 5 , a diagram illustrating RR intervals between QRScomplexes in accordance with one or more embodiments will be discussed.After the main template has been identified as determined according tomethod 400 of FIG. 4 above, the main template can be used to determineRR intervals between consecutive normally conducted QRS complexes todetermine whether the patient 110 is experience atrial fibrillation(AF). FIG. 5 shows an example of an RR interval between two successiveQRS complexes, QRS complex 510 and QRS complex 512. The RR interval 518between these two QRS complexes is the time between the R peaks of eachof the QRS complexes. It should be noted that although the minimum pointin the QRS complex can be used as the fiducial point 310, since thepolarity is determined by the way differential vectors are formed, otherfiducial points can be used other than the minimum point. The RRinterval 518 between multiple consecutive QRS complexes can bedetermined as discussed with respect to FIG. 6 , below.

Referring now to FIG. 6 , a diagram of a method to identify RR intervalsbetween similar QRS complexes in accordance with one or more embodimentswill be discussed. Although FIG. 6 shows one implementation of method600, method 600 can include more or fewer operations than shown andvarious other orders of the operations than shown, and the scope of thedisclosed subject matter is not limited in these respects. Method 600can be performed after the main template is identified according tomethod 400 of FIG. 4 . In some embodiments, after a template of theselected channel is formulated, normally conducted QRS complexes can beidentified, and the rhythm can be classified as described below todistinguish between AF and various SVT rhythms. In some embodiments, thetemplate formulation process can be performed as described in U.S.Provisional Application No. 62/890,313 filed Aug. 22, 2019 “CardiacMonitoring System with Normally Conducted QRS Complex Identification”.Although only one channel is described for illustration, in someexamples multiple channels can be used. In some embodiments, fourchannels can be used out of six possible differential channels formedfrom four independent electrodes placed around the chest of a patient110. In other embodiments, a different number of channels, includingonly one channel, can be used. In WCM embodiments, a different number ofelectrodes can be used, often a reduced number of electrodes, or adifferent garment system can be used compared to the garment or supportstructure 112 shown in FIG. 1 .

At operation 610, the main template can be applied to each QRS complexin a given segment of QRS complexes. The FCC values of each of the QRScomplexes can then be calculated, or alternatively SCC values can becalculated in some embodiments. At operation 612, if the FCC value (orSCC value) for a QRS complex is greater than 0.9 or some threshold, thenthat QRS complex can be considered as a normally conducted QRS complex,and can be labeled as a supraventricular (SV) complex, meaning that theQRS complex is a normally conducted QRS complex that originate above thesinoatrial (SA) node. It should be noted that although an FCC value (oran SCC value) of 0.9 can be used as a matching or correlation thresholdas an example, other values for the FCC or SCC can be used as athreshold, and the scope of the disclosed subject matter is not limitedin this respect. For example, an FCC range of 0.8 to 0.9 can be used,and an SCC range of 0.9 to 0.95 can be used. At operation 614, the RRintervals 518 between consecutive SV complexes can be calculated, andthe RR intervals can be labeled as SV RR intervals. It should be notedthat QRS complexes having FCC values (or SCC) values below thethreshold, such as having value below 0.9, are disregarded since suchuncorrelated QRS complexes can be considered as not being normallyconducted QRS complexes or otherwise are noisy.

At operation 616, the highest 25 percent of RR intervals in the ECGsegment can be identified. In some embodiments, this threshold can rangefrom about 20 percent to about 30 percent, and the scope of thedisclosed subject matter is not limited in this respect. At operation618, for each identified RR interval, the atrial waveform can be savedin a window between 260 ms and 120 ms from the fiducial point of thesecond SV complex of an RR interval. In some embodiments, the window canbe defined to have a range large enough to capture the P-waves alongwith the QRS complexes. At operation 620, the P-wave range can bemeasured during normal sinus rhythm (NSR) and saved as described aboveto be used later for SVT rhythm classification.

Referring now to FIG. 7 and FIG. 8 , a diagram of an ECG signal atdifferent scales and the HR variability of the ECG signal in accordancewith one or more embodiments will be discussed. Current American HeartAssociation (AHA) guidelines define the presence of atrial fibrillation(AF) as electrocardiographic documentation of absolutely irregular RRintervals and no discernible, distinct P waves lasting for at least 30seconds. In some embodiments, the RR intervals and RR intervalvariability of consecutive normally conducted QRS complexes can bemeasured. Furthermore, since AF and some other supraventriculartachycardia (SVT) rhythms are not an immediately life-threateningarrhythmia, detecting the onset of AF or such SVT rhythms is generallynot critical. Accordingly, real time approaches for classifying theserhythms are not used in some embodiments. For example, a segment-basedapproach with relatively long segments, for example over one minutelong, can be used.

High heart rate (HR) variability has been observed in AF and in otherSVT rhythms, so HR variability alone is not used to classify the rhythmin some embodiments. For example, the rhythm shown in FIG. 7 has adistinctive atrial depolarization waveforms, which indicates the rhythmis not AF. The same rhythm is shown in FIG. 8 using a different scale.The HR variability is shown right bottom chart which shows a high HRvariability which is similar to AF. In accordance with some embodiments,identify normally conducted QRS complexes can be identified and combinedwith P-wave analysis to classify rhythms into AF and other SVT rhythmswith enhanced accuracy.

Referring now to FIG. 9 , a diagram of a method for SVT rhythmclassification in accordance with one or more embodiments will bediscussed. Although FIG. 9 shows one implementation of method 900,method 900 can include more or fewer operations than shown and variousother orders of the operations than shown, and the scope of thedisclosed subject matter is not limited in these respects. At operation910, the variability of the RR intervals can be referred to as HRvariability such that the HR variability can be identified from the RRintervals between the SV complexes.

In some embodiments, at operation 912 an atrial template can beformulated for example using the template formation method 400 of FIG. 4. If the atrial template range is small, then the rhythm can beclassified as AF at operation 914 in one or more embodiments. An exampleof a P-wave template is shown in and described with respect to FIG. 11 ,below. At operation 916, to further enhance specificity the atrialtemplate waveforms can be compared. If the atrial template waveforms arenot similar, then the rhythm can be classified as AF at operation 918.After formulating the atrial templates, if the HR variability is highand the atrial template range is not small, then the rhythm can beclassified as not AF at operation 920 in some embodiments. Anotherexample of P-wave templates is shown in and described with respect toFIG. 12 below.

At operation 922, if the atrial template waveforms are similar, then therhythm can be classified as not AF. In some embodiments, this rhythm canbe an SVT rhythm such as premature atrial contraction (PAC). In otherembodiments, the atrial waveforms can be compared to a stored P-wavefrom a normal sinus rhythm (NSR) at operation 924. If the atrialwaveform is similar to the P-wave, then the rhythm can be classified asa sinus rhythm with varying RP intervals at operation 926.

Referring now to FIG. 10 , a diagram of an additional method for SVTrhythm classification in accordance with one or more embodiments will bediscussed. Although FIG. 10 shows one implementation of method 1000,method 1000 can include more or fewer operations than shown and variousother orders of the operations than shown, and the scope of thedisclosed subject matter is not limited in these respects. At operation1010, if RR interval variability high and the RR intervals are integermultiple of the shortest RR interval, then the rhythm can be classifiedas atrial flutter (AFL). At operation 1012, in some embodiments, theatrial template can be compared to a stored P-wave or P-wave templatetaken during NSR. At operation 1014, if the atrial template is differentfrom the P-wave and smaller, then the rhythm can be classified as AFL insome embodiments. At operation 1016, if the RR interval is stable andthe HR is very high, for example higher than 180 bpm, then the rhythmcan be classified as AFL or atrial tachycardia (AT) AF as a furtherrefinement in some embodiments. In some embodiments, if RR intervalvariability is high, at operation 1018 atrial waveforms can be analyzedfor similarity for example when the RR intervals are all within the 10%of the median RR interval. At operation 1020, if the atrial waveformsare similar then the rhythm can be classified as Wenckebach in someembodiments. It should be noted that other SVT rhythm can be detectedusing HR, HR variability, RR interval patterns, or atrial templatecompared to P-wave template, and the scope of the disclosed subjectmatter is not limited in this respect. In some embodiments, the methodsdescribed herein can implemented by cardioverter defibrillator, forexample as shown in and described with respect to FIG. 2 . In suchembodiments, the cardioverter defibrillator can comprise a housing tocontain a processor, a memory, and a high voltage subsystem, andoptionally other components shown for example in FIG. 2 . In someembodiments, the housing can be affixable to a body or skin of thepatient via an adhesive. In other embodiments, the housing can beimplantable in a subcutaneous location of a body of the patient. Itshould be noted that these embodiments are some examples of a cardiacmonitoring system or a cardioverter defibrillator, and the scope of thedisclosed subject matter is not limited in these respects.

Referring now to FIG. 11 , a diagram of example atrial templatesincluding P-wave templates in accordance with one or more embodimentswill be discussed. Three examples from the same patient are shown inFIG. 11 with 10× magnification of the P-wave templates. The P-wavetemplates of each of the examples show a relatively small the P-waverange and varying morphology. If the P-wave template of the received QRScomplex window is less than a threshold percentage, for example 25% insome embodiments, of the stored P-wave range measured during normalsinus rhythm (NSR) and shown in the windows shown in the charts of FIG.11 , then the rhythm can be classified as AF.

FIG. 12 is a diagram of additional examples of atrial templatesincluding P-wave templates in accordance with one or more embodiments.The charts of FIG. 12 show another example of three measurements fromthe same patient, but a different from the patient of FIG. 11 . FIG. 12shows a similar amplitude of P-wave templates, for example larger than50% of the P-wave range measured from NSR as previously described, andthe consistent morphology. In one or more embodiments, these rhythms areclassified as not AF.

Although the claimed subject matter has been described with a certaindegree of particularity, it should be recognized that elements thereofmay be altered by persons skilled in the art without departing from thespirit and/or scope of claimed subject matter. It is believed that thesubject matter pertaining to a cardiac monitoring system withsupraventricular tachycardia (SVT) classifications and many of itsattendant utilities will be understood by the forgoing description, andit will be apparent that various changes may be made in the form,construction and/or arrangement of the components thereof withoutdeparting from the scope and/or spirit of the claimed subject matter orwithout sacrificing all of its material advantages, the form hereinbefore described being merely an explanatory embodiment thereof, and/orfurther without providing substantial change thereto. It is theintention of the claims to encompass and/or include such changes.

What is claimed is:
 1. A cardiac monitoring system, comprising: aprocessor configured to receive a segment of an electrocardiogram (ECG)signal of a patient; a memory to store the segment of the ECG; whereinthe processor is configured to: identify normal sinus rhythm (NSR)complexes in the segment of the ECG signal as SV complexes; measure RRintervals between consecutive pairs of the SV complexes; determine RRvariability from the measured RR intervals between consecutive pairs ofthe SV complexes; obtain a P-wave waveform from a window of thecorresponding SV complex for each of the RR intervals; obtain a P-wavetemplate from the P-wave waveforms in the SV complexes; measure a rangeof the P-wave waveforms from the SV complexes; save the measured rangeof P-waves, the P-wave waveforms, and the P-wave template in the memory;and classify the identified SV complexes as either atrial fibrillation(AF) or supraventricular tachycardia (SVT) based at least on part theP-wave template and the RR variability; wherein the identified SVcomplexes are classified as AF when the RR variability is greater than athreshold value and an amplitude of the P-wave template is below apredetermined percentage of the P-wave range measured during NSR; andwherein the identified SV complexes are classified as SVT when the RRvariability is higher than the threshold value and the amplitude of theP-wave template is above the predetermined percentage of the P-waverange; and a support structure comprising a plurality of ECG electrodesconfigured to couple to a body of the patient through which the ECGsignal of the patient is obtained; wherein the support structurecomprises a plurality of defibrillation electrodes configured to coupleto the body of the patient, and a high voltage subsystem to apply adefibrillation voltage to the patient when a shockable event is detectedby the processor based at least in part on the classification of theidentified SV complexes.
 2. The cardiac monitoring system of claim 1,wherein: the identified SV complexes are classified as atrial flutter(AFL) when the RR variability is high, and the RR intervals are integermultiples of a shortest one of the RR intervals.
 3. The cardiacmonitoring system of claim 1, wherein the processor is furtherconfigured to: analyze the P-wave waveforms for similarity when the RRvariability is high; and wherein the identified SV complexes areclassified as Wenckebach when the P-wave waveforms are similar.
 4. Acardioverter defibrillator, comprising: a housing; a processor in thehousing configured to receive a segment of an electrocardiogram (ECG)signal of a patient; a memory in the housing to store the segment of theECG; and a high voltage subsystem in the housing to apply adefibrillation voltage to the patient; wherein the processor isconfigured to: identify normal sinus rhythm (NSR) complexes in thesegment of the ECG signal as SV complexes; measure RR intervals betweenconsecutive pairs of the SV complexes; determine RR variability from themeasured RR intervals between consecutive pairs of the SV complexes;obtain a P-wave waveform from a window of the corresponding SV complexfor each of the RR intervals; obtain a P-wave template from the P-wavewaveforms in the SV complexes; measure a range of the P-wave waveformsfrom the SV complexes; save the measured range of P-waves, the P-wavewaveforms, and the P-wave template in the memory; classify theidentified SV complexes as either atrial fibrillation (AF) orsupraventricular tachycardia (SVT) based at least on part the P-wavetemplate and the RR variability; wherein the identified SV complexes areclassified as AF when the RR variability is greater than a thresholdvalue and an amplitude of the P-wave template is below a predeterminedpercentage of the P-wave range measured during NSR; and wherein theidentified SV complexes are classified as SVT when the RR variability ishigher than the threshold value and the amplitude of the P-wave templateis above the predetermined percentage of the P-wave range; and apply thedefibrillation voltage to the patient when a shockable event is detectedbased at least in part on the classification of the identified SVcomplexes.
 5. The cardioverter defibrillator of claim 4, wherein thehousing includes an adhesive and is affixable to a body of the patientvia the adhesive.
 6. The cardioverter defibrillator of claim 4, whereinthe housing is implantable in a subcutaneous location of a body of thepatient.